Looking Beyond Disorder: Dynamics and Entropy in Glasses and Jamming
INVITED · W44 · ID: 1849798
Presentations
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From micro to mesoscale models of viscous liquid dynamics
ORAL · Invited
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Presenters
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Camille Scalliet
CNRS, ENS Paris
Authors
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Camille Scalliet
CNRS, ENS Paris
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Fluctuation near jamming
ORAL · Invited
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Publication: H. Ikeda, J. Chem. Phys 158 (5) (2023)
Presenters
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Harukuni Ikeda
Department of Physics, Gakushuin University
Authors
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Harukuni Ikeda
Department of Physics, Gakushuin University
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Permutation symmetry breaking and partial restoration in jammed systems
ORAL · Invited
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Presenters
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Varda F. Hagh
University of Illinois Urbana Champaign
Authors
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Varda F. Hagh
University of Illinois Urbana Champaign
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Sidney R Nagel
University of Chicago
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Role of a Structural Channel on Avalanche Dynamics Under Quasistatic Shear
ORAL · Invited
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Presenters
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Robert C Dennis
University of Pennsylvania and Syracuse University
Authors
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Robert C Dennis
University of Pennsylvania and Syracuse University
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Lisa Manning
Syracuse University
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Andrea J Liu
University of Pennsylvania
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Predicting dynamic heterogeneity at the glass transition temperature using machine learning
ORAL · Invited
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Publication: [1] V. Bapst et al. Unveiling the predictive power of static structure in glassy systems. Nat. Phys., 16(4):448–454, 2020.
[2] G. Jung, G. Biroli, and L. Berthier. Predicting dynamic heterogeneity in glass-forming liquids by physics-inspired machine learning. Phys. Rev. Lett., 130:238202, 2023.
[3] G. Jung, G. Biroli, and L. Berthier. Dynamic heterogeneity at the glass transition temperature predicted by transferable machine learning. (in preparation).Presenters
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Gerhard Jung
Laboratoire Charles Coulomb (L2C), CNRS Montpellier
Authors
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Gerhard Jung
Laboratoire Charles Coulomb (L2C), CNRS Montpellier
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